AI Agents & Automation
Agents that do real work, built in, not bolted on
We build agents, copilots, and AI features that are part of your product and operations, designed for trust, latency, and cost from the first sprint. Modern stack, strict TypeScript, measurable quality.
How our agents differ
LLM-native UX
Streaming responses, source citations, and graceful fallbacks. Interfaces users trust.
Engineering discipline
Next.js, TypeScript, and CI with evaluation suites that catch quality regressions before users do.
Cost & latency budgets
Model routing, caching, and token budgets treated as product requirements from day one.
What we ship
In-product copilots
Assistants embedded in your SaaS that act on user context.
Semantic search
Search that understands meaning across your content and documents.
Content workflows
Drafting, summarizing, and transforming content with human review built in.
Chat over private data
Secure conversational access to your internal knowledge.
From idea to launch
01
Scope
Define the job the AI does and how we will measure it.
02
Design
UX for trust: sources, confidence, and failure states.
03
Build
Iterative delivery with an evaluation harness on real data.
04
Launch & tune
Ship behind flags, watch quality and cost, iterate.
How we deliver
AI-native on every engagement
AI-assisted engineering
Every engineer works with Claude Code and Cursor. The repeatable parts go faster, and seniors focus on the hard ones.
Quality is measured
Evals and end-to-end tracing come standard, so quality, cost, and latency are numbers, not opinions.
People own the risk
Architecture, security, and reviews stay with senior engineers. AI accelerates, people decide.
Have a feature AI could transform?
Tell us the workflow. We will scope a copilot or search experience around it.